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Quantitative indicators are a common means of assessing the complex dimensions of a sustainable freshwater system, and framing scientific knowledge for policy and decision makers. There is an abundance of indicators in use, but considerable variation in terms of what is being measured and how indicators are applied, making it difficult for end-users to identify suitable assessment methods. We review 95 water-related indices and analyze them along their normative, procedural, and systemic dimensions to better understand how problems are being defined, highlight overlaps and differences, and identify the context(s) in which a particular index is useful. We also analyze the intended use, end-users, and geographic scale of application for each index. We find that risk assessment is the most common application (n = 25), with indices in this group typically focusing either on hazard identification (biophysical assessments) or vulnerability of human populations. Indices that measure freshwater ecological health are not explicitly linking these indicators to ecosystem services, and in fact the concept of ecosystem services is rarely (n = 3) used for indicator selection. Resource managers are the most common group of intended end-users (n = 25), but while 28 indices involved consultation with potential end-users, 11 did not specify an intended use. We conclude that indices can be applied as solution-oriented tools, evaluating scenarios and identifying tradeoffs among services and beneficiaries, rather than only assessing and monitoring existing conditions. Finally, earlier engagement of end-users is recommended to help researchers find the right balance among indices' salience, legitimacy, and credibility and thus improve their decision relevance.

Theoretical analyses and experimental studies of synthesized assemblages indicate that under particular circumstances species diversity can enhance community productivity through niche complementarity. It remains unclear whether this process has important effects in mature natural ecosystems where competitive feedbacks and complex environmental influences affect diversity-productivity relationships. In this study, we evaluated diversity-productivity relationships while statistically controlling for environmental influences in 12 natural grassland ecosystems. Because diversity-productivity relationships are conspicuously nonlinear, we developed a nonlinear structural equation modeling (SEM) methodology to separate the effects of diversity on productivity from the effects of productivity on diversity. Meta-analysis was used to summarize the SEM findings across studies. While competitive effects were readily detected, enhancement of production by diversity was not. These results suggest that the influence of small-scale diversity on productivity in mature natural systems is a weak force, both in absolute terms and relative to the effects of other controls on productivity.